The study aims to conduct a practical test of the Resource Analysis and Management (RAM) methodology. This article presents the importance of assessing resource provision as one of the priority tasks in managing economic growth and ensuring national security. The methodology is based on a comparative analysis of the development resources of various economic entities within a unified environment. A direct assessment of selected resources was carried out using hostility coefficients. For comparison purposes, official data from international organizations, major companies, and analytical centers in Russia, the United States, and China were used. The results obtained may contribute both to identifying the main directions for changes in the economic mechanisms of the Russian Federation in the interests of economic growth and economic security, and to implementing objectives aimed at achieving technological leadership.

The relevance of this study stems from the need to improve the effectiveness of responses to large-scale crisis phenomena under which the Russian economy has operated over the past six years. The purpose of the study is to identify and characterize the key directions for adapting the Russian public administration system to contemporary complex conditions. The subject of the research is a comprehensive analysis of the Russian economy, ranging from mapping methodologies to the digitalization of public administration. The study concludes that the effectiveness of Russian public administration under crisis conditions may be enhanced through the implementation of a hybrid governance model in which centralized management within a mobilization economy framework is complemented by a buffer of flexible public policy instruments. Such a combination may reduce the response time of the public administration system to crisis situations both through rapid centralized decision-making and through flexible and timely responses to evolving crisis dynamics. The findings of the study may be useful for representatives of public authorities, crisis management specialists, and analysts involved in the development of public administration systems.

Purpose: This study examines the influence of government fertility policies on total fertility rates (TFR) across seven culturally diverse countries: South Korea, Japan, Singapore, Russia, France, Sweden, and Canada, analyzing policy effectiveness and implementation patterns from 1970 to 2024. Design/methodology/approach: The research employs a dual methodological approach combining systematic literature review with comparative policy analysis. Fertility policies are categorized into material policies (financial incentives) and humanistic care policies (work-life balance support). The study analyzes policy implementation timing and corresponding TFR changes, utilizing longitudinal data from UN population statistics. Findings: The analysis reveals a consistent 10‑year lag between policy implementation and observable TFR impacts. Material policies, including newborn bonuses and childcare allowances, show varying effectiveness across countries. Nations implementing comprehensive approaches combining material and humanistic policies (France, Sweden) maintained higher TFR levels compared to those focusing primarily on financial incentives (South Korea, Japan). Despite significant policy investments, East Asian countries continue struggling with sub‑1.0 TFR, suggesting the influence of broader sociocultural factors. Research limitations: The study’s focus on seven countries, while representing diverse cultural zones, may limit generalizability to other contexts. Additionally, some statistical data and benefit amounts cited in this study may not reflect the most recent policy updates, as government programs are frequently revised. Readers should consult official government sources for the latest figures. Practical implications: The findings indicate that successful fertility policies require both immediate financial support and long-term societal adaptation measures, emphasizing the need for policy patience in evaluating effectiveness. Specifically, countries that combine material incentives with humanistic care policies (e. g., France and Sweden) demonstrate higher TFR levels, while nations relying primarily on financial measures (e. g., South Korea and Japan) show limited success despite substantial investment. The study contributes to the theoretical understanding of the dual-dimensional policy framework (material vs. humanistic) and provides evidence-based recommendations for designing integrated fertility policies that address both economic barriers and sociocultural factors. Originality/value: This research uniquely categorizes fertility policies into material and humanistic approaches while establishing a clear temporal relationship between policy implementation and fertility outcomes. The study’s longitudinal analysis provides valuable insights into policy effectiveness across different cultural contexts, contributing to evidence-based fertility policy design.

The purpose of this study is to examine the specific features of maintaining and assessing the financial stability of oil and gas companies under conditions of economic instability, as well as to identify the stages most suitable for the implementation of neural networks. The practical significance of the research lies in creating the prerequisites for the subsequent development and implementation of regulatory and methodological tools aimed at ensuring the financial stability of sectoral enterprises. Potentially, this may serve as an instrument for promoting economic development at the macroeconomic level. The findings of the study may be used by financial analysts and government regulators in assessing and managing industry-specific risks, as well as by investors and credit institutions in evaluating the financial stability of enterprises in the energy sector. However, models trained on data from relatively developed markets (such as Russia and the Gulf countries) have certain limitations, namely the possibility of reduced accuracy when applied to developing economies (for example, Angola).

The purpose of this study is to identify the institutional features of the current risk management system employed by the Federal Treasury in managing budget liquidity and to substantiate directions for its improvement, taking into account the need to maintain a balance between the security of budgetary funds and the efficiency of financial operations. The study examines the basic and advanced risk management models applied to operations conducted both on organized and over-the-counter markets, as well as the mechanism of risk hedging through repurchase agreements (repo transactions). The paper identifies the specific features of the current approach, which is based on the use of the infrastructure of the non-bank credit institution acting as a central counterparty, the National Clearing Centre, as well as on capital adequacy requirements and credit ratings of credit institutions. It is substantiated that the existing system demonstrates high effectiveness in terms of safeguarding budgetary funds; however, it is characterized by a limited capacity to respond promptly to changes in the financial market due to its dependence on external information sources and the prevailing practice of risk transfer. Based on the analysis conducted, the study formulates directions for modernizing the system, including monitoring decisions of the Bank of Russia regarding financial market participants, consolidating information on the compliance of credit institutions with established requirements, and implementing a risk-oriented adjustment of operational parameters when placing temporarily available budget balances within the framework of existing regulatory and legal provisions. The findings may be useful primarily for the Federal Treasury and other public authorities engaged in budget liquidity management, as well as for researchers in the fields of public finance, risk management, and budget liquidity management.

The purpose of this study is to identify the key problems associated with managing the saving behavior of Russian citizens under conditions of macroeconomic instability and to develop recommendations for improving savings policy. The study is based on a systems approach and employs methods of statistical and comparative analysis, as well as elements of econometric modeling. The empirical basis of the research was formed using data from NAFI, statistics from the Bank of Russia, and Rosstat. The results reveal structural changes in household saving preferences and identify four key groups of problems: declining real incomes, the gap between financial literacy and actual financial behavior, inflationary erosion of savings, and the concentration of risks and fraud. Correlation and regression analysis demonstrates that the most significant factors reducing the household saving rate are increasing debt burden and elevated consumer expectations, whereas the impact of the key interest rate remains limited (with an elasticity of approximately 0.375). The authors propose a set of measures aimed at developing targeted savings instruments, strengthening cybersecurity, and improving long-term investment instruments. The findings of this study may be useful to a broad range of specialists, including representatives of public authorities and regulatory agencies, employees of banks, investment companies and asset management funds, as well as academics, marketers, economists, sociologists, psychologists, and specialists in behavioral economics.

This article is devoted to developing conceptual approaches to selecting a prototype for an integrated platform of the Unified Digital Data System of Economic Entities in Russia (UDDS EE). The object of the study is the system of digital services and platforms that serves as the technological foundation of the «Government as a Platform» governance concept. The study aims to substantiate the procedure for the formation and operation of an integrated UDDS EE platform designed to enhance the efficiency of public administration within the framework of interagency cooperation. The research results include the substantiation of the architecture and the fundamental principles underlying the formation and use of the UDDS EE based on the interaction of three platform components. Through comparative analysis of technological and platform solutions, as well as an examination of international experience and domestic practices in integrating economic entities’ data, the study demonstrates the feasibility of adopting an «integration-based scenario» for developing the platform of the Unified Digital Data System of Russian organizations. It further justifies a three-component platform model aimed at establishing a state-level infrastructure with rigorous information quality control mechanisms. The article proposes directions for transforming interagency cooperation, identifies potential areas of application, and discusses the challenges and barriers that may arise during the implementation of the proposed platform model for the Unified Digital Data System of Russian organizations. The expected benefits and effects of its deployment are also outlined. The findings may be of interest to public authorities, professional communities, investors, and other stakeholders involved in economic and business activities.

Digital intellectual assets (DIAs) generate business added value, contribute to the intellectualization of production processes, and ultimately enable industrial enterprises to achieve technological leadership and high-order competitive advantages. The purpose of this study is to identify the specific features of DIAs as instruments of smart manufacturing and, on this basis, to determine the models and principles for their commercialization. The methodological framework of the study is based on methods of classification, comparative analysis, generalization, and systematization. The research identifies the criteria distinguishing digital technologies from digital intellectual assets and characterizes the distinctive features of resource-based, innovation-driven, platform-based, investment-oriented, and ecosystem approaches to DIA commercialization. In addition, a comparative analysis of traditional and digital commercialization models for DIAs is conducted, highlighting their respective advantages and disadvantages. The study concludes that the selection of a particular commercialization concept and model depends on the maturity level of a specific type of DIA, the degree of enterprise digitalization, and the market environment. The authors also propose an original classification of the principles underlying DIA commercialization. The findings of the study may be useful for company executives across various sectors of the economy in developing their own strategies for the commercialization of digital intellectual assets.

The aim of this study is to analyse the evolution of methods for building recommender systems and approaches to evaluating their performance under conditions of multi-criteria decision-making and dynamically changing user preferences. The paper examines the key stages in the development of recommender technologies and systematises modern algorithms and architectures, including hybrid, neural network-based, and graph-based models. Particular attention is paid to methods for evaluating recommendation quality and to the classification of metrics reflecting accuracy, ranking quality, diversity, and computational efficiency. The study demonstrates that reliance solely on accuracy metrics is insufficient for an adequate assessment of recommender system performance. The authors address key methodological challenges, including the coldstart problem, data sparsity, and the need to balance accuracy and diversity in recommendations. The paper concludes that a comprehensive multi-criteria approach is essential for the effective evaluation of recommender systems. The findings may be useful for researchers, recommender system developers, and specialists in machine learning and data analysis, as well as for business practitioners involved in selecting and evaluating the effectiveness of recommendation algorithms.

In the context of digitalization and the increasing complexity of software development processes, Data Governance is becoming a strategic priority for the development of Russian digital and high-tech companies. Drawing on recent studies in Business Intelligence and Data Governance, as well as empirical evidence from the implementation of Business Intelligence systems in software quality management and human resource analytics (HR analytics) within a telecommunications company, the authors substantiate an integrated model of data governance encompassing strategic, technological, and socio-cultural (human capital) levels, which constitutes the main objective of the study. The article conceptualizes the «art of managing data» as an instrument of strategic management and concludes that Data Governance should be understood not only as a technological framework but also as a socio-managerial process that shapes an organization’s decision-making culture. The findings of the study may be applied in the development of corporate digital governance strategies and the design of Data Governance systems

The emergence and dominance of the digital economy mark a transition from traditional factors of production (land, labour, and capital) to a new key resource – intellectual capital (IC). In contemporary conditions, it is intellectual capital, rather than tangible assets, that serves as the primary source of competitive advantage, sustainable development, and consistently high corporate value. This article examines the transformation of the role of intellectual capital within the digital economy. IC management is considered a prerequisite for the strategic development of businesses, aimed at creating an environment conducive to the effective development of human capital and its realization in the creation of intellectual products. The purpose of the study is to analyse the impact of digital technologies on the key components of intellectual capital, namely human, structural, relational, and customer capital. The object of the research is the intellectual capital of an organization as an economic category, while the subject comprises the set of methods, tools, and relationships that emerge in the process of managing IC in the context of the digital economy. The study employs general scientific methods, including analysis, synthesis, comparison, classification, and modelling. The results propose new approaches to the assessment and management of intellectual capital, based on data-driven solutions and integration into digital ecosystems, as well as practical recommendations for building an effective management system.

This article addresses the problem of insufficient alignment between intellectual property (IP) management processes and research and development (R&D) activities in high-tech enterprises, as well as the lack of formalized consideration of technology and engineering maturity levels in organizational decision-making. These factors hinder the optimization of IP portfolios and lead to reduced effectiveness in the commercialization of intellectual outputs (results of intellectual activity, RIA). The relevance of this issue is driven by intensifying competition and the growing need to enhance the efficiency of R&D operations in knowledge-intensive firms. The aim of the study is to design an IP management system for such enterprises, incorporating the development of an integrated organizational framework and the formalization of lifecycle-related tasks associated with RIA. The study proposes a structural-functional model that captures the interdependencies between IP coordination tasks and the stages of the RIA lifecycle within a comprehensive R&D management system at a high-tech enterprise. The findings provide a foundation for the development of a set of interconnected models and algorithms implementing an integrated IP management approach. This approach ensures the alignment of scientific-technical, legal, and economic logics of management, while improving coordination across the lifecycle of intellectual outputs.

The subject of the study is tax and budgetary instruments aimed at stimulating the development of human capital in knowledge-intensive sectors of the economy. The purpose of the study is to diagnose fiscal instruments for human capital stimulation in order to identify the institutional constraints of state financial support that hinder the development of employee competencies in knowledge-intensive industries. The study employs the following methods: analysis of academic publications and regulatory legal documents related to state support for the efficient utilization of employee competencies in knowledge-intensive sectors of the economy; and empirical analysis of the impact of tax and budgetary preferences on human capital development in the context of achieving technological sovereignty and technological leadership. The paper provides a literature review covering the following aspects of the research problem: the efficient utilization of employee competencies in knowledge-intensive industries; the influence of tax and budgetary incentives on human capital development aimed at achieving technological sovereignty and leadership; and the separation of the effects of state financial support for the objective assessment of its role in stimulating intellectual capital. The study identifies limitations associated with the ecosystem-based nature of tax and budgetary instruments designed to promote human capital development in knowledge-intensive industries for the achievement of technological sovereignty and leadership. The findings of the study may be useful for employees of financial authorities, lecturers in economics-related disciplines, and students specializing in management, law, and economics.

The evaluation of organizational performance (of a company or enterprise) under conditions of uncertainty (information entropy), as well as latent and/or explicit data inconsistency, may involve the following risks: misleading both external and internal stakeholders; reliance on low-quality, inaccurate, and ultimately ineffective results of business performance analysis; and inadequate assessment of indicators of financial performance. As a consequence, a symmetry of misconceptions regarding particular assets and the company’s overall financial performance emerges, leading stakeholders to make incorrect managerial and/or investment decisions, inappropriate optimization decisions, and potentially resulting in violations of stakeholder rights. The purpose of this study is to examine approaches to the mathematical modeling of the relationship between a company’s financial performance and the quality of information support (data value). The research employed general scientific research methods, as well as a methodological approach to substantiating managerial and/or investment decision-making under conditions of informational data entropy. The authors propose an approach based on the application of mathematical tools for analyzing the interrelationships among various factors affecting organizational performance evaluation and the quality of information support (data value). The implementation of the study’s findings will enable enterprises to improve such indicators as operational efficiency, financial sustainability, solvency, and others at a specific stage of the company’s life cycle.

The purpose of this study is to analyze a human resource management (HR) tool and an element of managerial controlling architecture in organizations in Central and Eastern European (CEE) countries – digital outsourcing. The relevance of the research lies in defining its applied management context, including decision-making, responsibility allocation, control mechanisms, and building trust in the «company-customer – digital service provider» relationship. Based on the analysis of digital HR outsourcing practices, including payroll, HR electronic document management and the use of intelligent HR platforms, it is shown that the digitalization of the external course of processes is accompanied by a change in the logic of management control. This is reflected in the shift of the latter from operational monitoring to risk-oriented and predictive models. In the course of the study, the management paradox of digital outsourcing was revealed, which consists in the fact that the transfer of operational functions to an external provider does not lead to a decrease in the managerial responsibility of the customer company, but, on the contrary, increases the requirements for manageability, data interpretation and institutionalized control of decisions. The author of the article shows that in the CEE countries the effectiveness of digital outsourcing is determined not by the level of technological automation of HR processes, but by the quality of the corporate governance architecture and the development of a management controlling system. The results obtained are of practical importance for organizations implementing digital outsourcing of HR functions in the institutionally heterogeneous environment of the CEE countries.

Purpose: This paper aims to contribute to the ongoing discourse on wage determination by proposing a topical approach that incorporates three key factors, working hours, education, and experience, and to provide a robust, strategic, evidence-based framework for formulating wage improvement policies. Methodology: Using a rigorous econometric approach, we analyze a dataset comprising 545 observations of full-time employed males from the National Longitudinal Survey of Youth, spanning 1980 to 1987. We then apply the results of their combined effects to derive detailed explanatory guidelines. Findings: The results reveal a statistically significant negative relationship between annual hours worked and wages, indicating diminishing returns to earnings as working hours increase. In contrast, education and experience exhibit strong positive correlations with wages, with each additional year of education associated with a 10.55% increase in earnings, and each additional year of experience linked to a 13.81% wage increase. Notably, the non-linear experience-wage relationship demonstrates diminishing returns at higher levels of experience. Originality and contribution: The study introduces a novel framework emphasizing that the marginal utility of working hours varies with educational attainment, and that the quality of experience is shaped both by the number of hours worked and the conditions under which those hours are performed. Additionally, the concept of the experience-education multiplier effect highlights how education amplifies the value of experience, particularly in knowledge-intensive sectors.

The relevance of this study is determined by the fact that the domestic tourism sector in Russia is one of the priority branches of the national economy. The aim of the paper is to identify the key stages and specific features of strategic management of tourism territory development in the Russian Federation. The author examines statistical data on domestic tourism, analyses the regulatory and legislative framework governing the development of the sector in Russia, and identifies the key characteristics and principles of strategic management at both federal and regional levels. Structural models are proposed for each level. The results of the study may be of practical use for researchers, entrepreneurs, as well as regional and municipal authorities in the development of tourism-related projects.